Automated assessment of laparoscopic pattern cutting skills using computer vision and deep learning.

Journal: Surgery
Published Date: Jul 10, 2025

Abstract

BACKGROUND: Pattern cutting assessment in Fundamentals of Laparoscopic Surgery currently relies on manual measurement, which can be time-consuming and prone to variability and human error. An automated, objective assessment system could enhance the efficiency, reliability, and standardization of surgical skills evaluation.

Authors

  • Fuat Uyguroglu
    Department of Industrial and Systems Engineering, University of Miami, Coral Gables, FL. Electronic address: fxu36@miami.edu.
  • William Joseph Hoy
    Department of Industrial and Systems Engineering, University of Miami, Coral Gables, FL.
  • Adam Meyers
    Department of Industrial and Systems Engineering, University of Miami, Coral Gables, FL.
  • Cheng-Bang Chen
  • Nurcin Celik
    Department of Industrial and Systems Engineering, University of Miami, Coral Gables, FL.
  • M Carolina Jimenez
    DeWitt Daughtry Family Department of Surgery, Miller School of Medicine, University of Miami, Miami, FL.
  • José M Martínez
    Video Processing and Understanding Lab, Universidad Aut́onoma de Madrid 28049 Madrid, Spain.
  • Daniel Sleeman
    DeWitt Daughtry Family Department of Surgery, Miller School of Medicine, University of Miami, Miami, FL.
  • Laurence R Sands
    DeWitt Daughtry Family Department of Surgery, Miller School of Medicine, University of Miami, Miami, FL.
  • Onur C Kutlu
    DeWitt Daughtry Family Department of Surgery, Miller School of Medicine, University of Miami, Miami, FL.
  • Mehmet Akcin
    Department of Industrial and Systems Engineering, University of Miami, Coral Gables, FL; DeWitt Daughtry Family Department of Surgery, Miller School of Medicine, University of Miami, Miami, FL.

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